Python and HDF5: Unlocking scientific data (Record no. 2459)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01762nam a22002057a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200219164734.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 200117b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 978-93-5110-385-1 |
| 028 ## - PUBLISHER NUMBER | |
| Source | Allied Informatics, Jaipur |
| Bill Number | 7084 |
| Bill Date | 13/01/2020 |
| Purchase Year | 2019-20 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | BSDU |
| Language of cataloging | English |
| Transcribing agency | BSDU |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 005.133 |
| Item number | COL |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Collette, Andrew |
| 245 ## - TITLE STATEMENT | |
| Title | Python and HDF5: Unlocking scientific data |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Mumbai |
| Name of publisher, distributor, etc. | Shroff Publishers & Distributors Pvt. Ltd. |
| Date of publication, distribution, etc. | 2014 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 135 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Gain hands-on experience with HDF5 for storing scientificdata in Python. This practical guide quickly gets you up to speed on thedetails, best practices, and pitfalls of using HDF5 to archive and sharenumerical datasets ranging in size from gigabytes to terabytes. Through real-world examples and practical exercises, you’ll explore topics suchas scientific datasets, hierarchically organized groups, user-defined metadata,and interoperable files. Examples are applicable for users of both Python 2 andPython 3. If you’re familiar with the basics of Python data analysis, this isan ideal introduction to HDF5. •Get set up with HDF5 tools and create your first HDF5file •Work with datasets by learning the HDF5 Dataset object •Understand advanced features like dataset chunking andcompression •Learn how to work with HDF5’s hierarchical structure,using groups •Create self-describing files by adding metadata with HDF5attributes •Take advantage of HDF5’s type system to createinteroperable files •Express relationships among data with references, namedtypes, and dimension scales •Discover how Python mechanisms for writing parallel codeinteract with HDF5 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Python |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | |
| Koha item type | Books |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Date acquired | Cost, normal purchase price | Full call number | Barcode | Date last seen | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BSDU Knowledge Resource Center, Jaipur | BSDU Knowledge Resource Center, Jaipur | General Stacks | 2020-01-17 | 275.00 | 005.133 COL | 018013 | 2020-02-12 | 275.00 | 2020-01-17 | Books |